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International Conference on Web Information Systems and Mining

WISM 2012: Web Information Systems and Mining pp 472–479Cite as

Data Profiling for Semantic Web Data

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7529))

Abstract

Lots of RDF data have been published in the Semantic Web. For human users it is often rather difficult to get the big picture of a large RDF data exposed by Semantic Web applications. How to understand a large and unfamiliar RDF data becomes very important when the data schema is absent or different schemas are mixed. In this paper we describe a tool which can induce the actual schema, gather corresponding statistics, and present a UML-based visualization for the RDF data sources like SPARQL endpoints and RDF dumps. Experimental results, using six data sets from the Linked Data cloud, compare our approach and ExpLOD. The evaluations show that our approach is more efficient than ExpLOD.

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Author information

Authors and Affiliations

  1. School of Computer Science and Engineering, Southeast University, Nanjing, 210096, P.R. China

    Huiying Li

Authors
  1. Huiying Li
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Editor information

Editors and Affiliations

  1. Deaprtment of Business Administration, Caritas Institute of Higher Education, 18 Chui Ling Road, Tseung Kwan O, Hong Kong, China

    Fu Lee Wang

  2. School of Computer and Information Engineering, Shanghai University of Electric Power, 200090, Shanghai, China

    Jingsheng Lei

  3. Department of Computer and Inforamtion Science, University of Macau, Av. Padre Tomás Pereira, Taipa, Macau, China

    Zhiguo Gong

  4. School of Computer, Shanghai University, 200444, Shanghai, China

    Xiangfeng Luo

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© 2012 Springer-Verlag Berlin Heidelberg

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Li, H. (2012). Data Profiling for Semantic Web Data. In: Wang, F.L., Lei, J., Gong, Z., Luo, X. (eds) Web Information Systems and Mining. WISM 2012. Lecture Notes in Computer Science, vol 7529. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33469-6_59

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  • DOI: https://doi.org/10.1007/978-3-642-33469-6_59

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-33468-9

  • Online ISBN: 978-3-642-33469-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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